scholarly journals Recommendations for Improving Integration in National End-to-End Flood Forecasting Systems: An Overview of the FFIR (Flooding From Intense Rainfall) Programme

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 725 ◽  
Author(s):  
David Flack ◽  
Christopher Skinner ◽  
Lee Hawkness-Smith ◽  
Greg O’Donnell ◽  
Robert Thompson ◽  
...  
Keyword(s):  
Surface Water ◽  
Lead Time ◽  
End Users ◽  
Intense Rainfall ◽  
Weather Forecasts ◽  
Propagation Of Uncertainty ◽  
Effective Dissemination ◽  
Forecasting System ◽  
End To End ◽  
The Uk

Recent surface-water and flash floods have caused millions of pounds worth of damage in the UK. These events form rapidly and are difficult to predict due to their short-lived and localised nature. The interdisciplinary Flooding From Intense Rainfall (FFIR) programme investigated the feasibility of enhancing the integration of an end-to-end forecasting system for flash and surface-water floods to help increase the lead time for warnings for these events. Here we propose developments to the integration of an operational end-to-end forecasting system based on the findings of the FFIR programme. The suggested developments include methods to improve radar-derived rainfall rates and understanding of the uncertainty in the position of intense rainfall in weather forecasts; the addition of hydraulic modelling components; and novel education techniques to help lead to effective dissemination of flood warnings. We make recommendations for future advances such as research into the propagation of uncertainty throughout the forecast chain. We further propose the creation of closer bonds to the end users to allow for an improved, integrated, end-to-end forecasting system that is easily accessible for users and end users alike, and will ultimately help mitigate the impacts of flooding from intense rainfall by informed and timely action.

Moving towards a fully probabilistic, end-to-end, impact-based, flood forecasting and warning system

2020 ◽  
Author(s):  
Charlie Pilling
Keyword(s):  
Warning System ◽  
Flood Forecasting ◽  
Incident Management ◽  
Probabilistic Forecasting ◽  
Worst Case ◽  
Forecasting System ◽  
End To End ◽  
Forecasting And Warning ◽  
Environment Agency ◽  
The Uk

<p>Set up in 2009, the UK Flood Forecasting Centre (FFC), is a successful partnership between the Environment Agency and the Met Office to provide national, operational, flood risk guidance. At the same time, we have a development programme to continuously improve flood forecasting. Operational for over a decade, the FFC has a strong portfolio and reputation amongst its users and customers. For example, the 2019 Responder Survey reported that 94% of those who have had contact with the FFC within the last 12 months are satisfied with the services provided.  </p><p>High impact, low probability events have been a feature of the first 10 years of the Flood Forecasting Centre. Probabilistic forecasting and risk-based approaches provide approaches to identify, forecast and warn for such events. Indeed, whilst these are currently successfully employed by various National Meteorological Hydrological Centres, there is also recognition (for example, World Meteorological Organisation) that effective forecasting and warning systems should be:</p><ul><li>‘<strong>impact-based’</strong>;</li> <li>driven by ensembles or realistic scenarios through an <strong>‘end-to-end’</strong> system (rather than precipitation ranges being simplified);</li> <li>more <strong>objective</strong>, so using new tools such as ensemble ‘sub-setting’, pattern recognition and machine learning to extract most value.</li> </ul><p>The Environment Agency is implementing a new Delft-FEWS forecasting system this year, termed Incident Management Forecasting System (IMFS). This will introduce a step change in capability for probabilistic impact-based forecasting. Initially, rainfall and coastal scenarios (termed ‘best-estimate’ and ‘reasonable worst case’) will be used to drive end-to-end forecasting, which includes for example impact data bases for property, infrastructure and communities. This is very much a stepping stone in the technical (systems) and adaptive (people, culture) transformation to a <strong>fully probabilistic, end-to-end, impact-based, flood forecasting. </strong></p><p>I will share some of our recent approaches to:</p><ul><li>objective, ensemble based, forecasting, including the Natural Hazards Partnership surface water hazard impact model (driven by the Met Office MOGREPS precipitation ensembles) which goes live this year;</li> <li>scenario generation and ensemble sub-setting to provide input to end-to-end, impact-based forecasting (IMFS);</li> <li>next steps in moving to a fully probabilistic, end-to-end, impact-based, flood forecasting and warning system</li> </ul><p>I will also highlight some of our current challenges that we would love to work with others to solve.</p>

scholarly journals Potential application of hydrological ensemble prediction in forecasting flood and its components over the Yarlung Zangbo River Basin, China

2018 ◽  
Author(s):  
Li Liu ◽  
Su L. Pan ◽  
Zhi X. Bai ◽  
Yue P. Xu
Keyword(s):  
River Basin ◽  
Lead Time ◽  
Flood Forecasting ◽  
Ensemble Prediction ◽  
Infiltration Capacity ◽  
Weather Forecasts ◽  
Flood Volume ◽  
Yarlung Zangbo River ◽  
Forecasting System

Abstract. In recent year, flood becomes a serious issue in Tibetan Plateau (TP) due to climate change. Many studies have shown that ensemble flood forecasting based on numerical weather predictions can provide early warning with extended lead time. However, the role of hydrological ensemble prediction in forecasting flood volume and its components over the Yarlung Zangbo River Basin (YZR), China has not been systematically investigated. This study adopts Variable Infiltration Capacity (VIC) model to forecast annual maximum floods (MF) and annual first floods (FF) in YZR based on precipitation, maximum and minimum temperature from European Centre for Medium-Range Weather Forecasts (ECMWF). N-simulations is proposed to account for more scenarios of parameters in VIC and shows improved flood simulation. Ensemble flood forecasting system can skilfully predict MF with a lead time of more than10 days, and has skill in forecasting the snowmelt-related components in about 7 days ahead. The accuracy of forecasts for FF is inferior with a lead time of only 5 days. The performance in 7-day accumulated flood volumes is better than the peak flows. The components in baseflow for FF are irrelevant to lead time, whilst for MF an obvious deterioration in performance with lead time can be perceived. The snowmelt-induced surface runoff is the most poorly captured component by the system, and the well-predicted rainfall-related components are the major contributor for good performance. From this study, it is concluded that snowmelt-induced flood volume plays an important role in YZR Basin especially in FF.

Weather forecasting and communication in the upper Great Ruaha catchment area.

2020 ◽  
pp. 217-234
Author(s):  
Anselm R. Mwajombe ◽  
Godwin A. Lema
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Weather Forecasting ◽  
Local Environment ◽  
Weather Forecast ◽  
Communication Technologies ◽  
End Users ◽  
Oral Traditions ◽  
Weather Forecasts ◽  
Effective Dissemination

Abstract Effective weather forecast dissemination depends on how effective dissemination channels are in informing decision making for improved management of water resources and livelihood activities, which depend on water resources in catchment areas. In this chapter, the effectiveness of the channels for weather forecast dissemination is assessed in terms of magnitude of awareness creation and versatility to end users. Our findings show that both traditional and conventional channels of weather forecasting and communication can be used to create awareness to end users in various parts of the country. For local communities, traditional weather forecasting and communicating were contingent on indigenous knowledge acquired through interaction with the local environment. Such information was accessed through indicators or signs that entail plant phenology, astronomical and meteorological events as well as mammals' behaviour. Conventional forecasting is communicated via modern communication technologies including radio, television, the Internet and posted letters. Communication of traditional weather forecasting is mainly through oral traditions. Results from our respondents revealed that 40% received weather forecasts through traditional channels, 11% through modern channels and 49% through modern and traditional channels. The majority of respondents said that weather forecasts from modern sources were not reliable to inform the decision-making process when compared with traditional sources. The study recommends synchronizing modern and traditional channels for effective weather forecast delivery.

Evaluation of convective lifecycles in convection permitting weather forecasts for tropical Africa.

2020 ◽  
Author(s):  
Peter Hill ◽  
Thorwald Stein ◽  
Carlo Cafaro ◽  
Beth Woodhams ◽  
Stuart Webster
Keyword(s):  
Large Scale ◽  
Weather Prediction ◽  
Local Population ◽  
Model Errors ◽  
Tropical Africa ◽  
Severe Storms ◽  
Weather Forecasts ◽  
Convective Systems ◽  
Forecasting System ◽  
The Uk

<p>Tropical Africa is subject to weather extremes at a variety of space- and time-scales, leading to droughts, floods and severe storms. The weather has a huge impact on the local population: droughts and floods impact on weather dependent industries such as agriculture or fishing, which much of the population rely on for their livelihoods, while severe storms can lead to destruction of property and even loss of life. Despite this, global numerical weather prediction performance remains notoriously poor in tropical Africa, particularly at smaller scales.</p><p>The UK Met Office has recently begun running an ensemble weather forecasting system for tropical Africa at convection permitting scale (4.4 km). This forecasting system clearly has enormous potential to enable improved weather forecasts in  tropical Africa. Previous studies indicate that convection permitting models can provide greater skill than lower resolution global models for sub-regions within tropical Africa. However, skill remains fairly poor and further evaluation work is necessary to identify potential model improvements.</p><p>This presentation describes an evaluation of the lifecycles of convective systems in the UK Met Office tropical Africa model. 10.8 micron brightness temperatures are used to identify and follow convective systems both in the model and in geostationary satellite observations, which provide both high temporal (15 minute) and spatial (~3 km) resolution. We evaluate the size, diurnal cycle, propagation, initiation and lifecycle of convective systems in the model and the link between these properties and the magnitude of surface precipitation produced. Finally we analyse and evaluate the response of storm systems and hence precipitation in the model to large scale atmospheric drivers such as the Madden-Julian Oscillation and African easterly waves. This process oriented evaluation helps identify of the causes of model errors, facilitating future improvements in the model.</p>

scholarly journals What do users think of the UK’s three COVID-19 contact-tracing apps? A comparative analysis

2021 ◽  
Vol 28 (1) ◽  
pp. e100320
Author(s):  
Vahid Garousi ◽  
David Cutting
Keyword(s):  
Mobile Apps ◽  
Analysis Data ◽  
End Users ◽  
Contact Tracing ◽  
User Reviews ◽  
The Public ◽  
Engineering Teams ◽  
Technical Issues ◽  
The Uk ◽  
The Right

ObjectivesOur goal was to gain insights into the user reviews of the three COVID-19 contact-tracing mobile apps, developed for the different regions of the UK: ‘NHS COVID-19’ for England and Wales, ‘StopCOVID NI’ for Northern Ireland and ‘Protect Scotland’ for Scotland. Our two research questions are (1) what are the users’ experience and satisfaction levels with the three apps? and (2) what are the main issues (problems) that users have reported about the apps?MethodsWe assess the popularity of the apps and end users’ perceptions based on user reviews in app stores. We conduct three types of analysis (data mining, sentiment analysis and topic modelling) to derive insights from the combined set of 25 583 user reviews of the aforementioned three apps (submitted by users until the end of 2020).ResultsResults show that end users have been generally dissatisfied with the apps under study, except the Scottish app. Some of the major issues that users have reported are high battery drainage and doubts on whether apps are really working.DiscussionTowards the end of 2020, the much-awaited COVID-19 vaccines started to be available, but still, analysing the users’ feedback and technical issues of these apps, in retrospective, is valuable to learn the right lessons to be ready for similar circumstances in future.ConclusionOur results show that more work is needed by the stakeholders behind the apps (eg, apps’ software engineering teams, public-health experts and decision makers) to improve the software quality and, as a result, the public adoption of these apps. For example, they should be designed to be as simple as possible to operate (need for usability).

The high-resolution COASTAL CRETE ocean forecasting system 

2021 ◽  
Author(s):  
Katerina Spanoudaki ◽  
George Zodiatis ◽  
Nikos Kampanis ◽  
Maria Luisa Quarta ◽  
Marco Folegani ◽  
...  
Keyword(s):  
High Resolution ◽  
Oil Spill ◽  
Hydrodynamic Model ◽  
Coastal Area ◽  
Eastern Mediterranean ◽  
End Users ◽  
Marine Conservation ◽  
Tourism Industry ◽  
Maritime Safety ◽  
Forecasting System

<p>The coastal area of Crete is an area of increasing interest due to the recent hydrocarbon exploration and exploitation activities in the Eastern Mediterranean Sea and the increase of the maritime transport after the enlargement of the Suez Canal. National and local authorities, like ports and the coast guard, who are involved in maritime safety, such as oil spill prevention, the tourism industry and policy makers involved in coastal zone management, are key end users’ groups who can benefit from high spatial and temporal resolution forecasting products and information to support their maritime activities in the coastal sea area of the island. To support local end users and response agencies to strengthen their capacities in maritime safety and marine conservation, a high-resolution, operational forecasting system, has been developed for the coastal area of Crete. The COASTAL CRETE forecasting system implements advanced numerical hydrodynamic and sea state models, nested in CMEMS Med MFC products and produces, on a daily basis, 5-day hourly and 6-hourly averaged high-resolution forecasts of important marine parameters, such as sea currents, temperature, salinity and waves. The COASTAL CRETE high-resolution (~ 1km) hydrodynamic model is based on a modified POM parallel code implemented by CYCOFOS in the Eastern Mediterranean and the Levantine Basin, while for wave forecasts, the latest ECMWF CY46R1 parallel version including a number of new features, a state-of-the-art wave analysis and prediction model, with high accuracy in both shallow and deep waters has been implemented with a resolution of ~1.8 km. The COASTAL CRETE hydrodynamic model has been evaluated against the CMEMS Med MFC model and with satellite Sea Surface Temperature data with good statistical estimates. The COASTAL CRETE wave model is calibrated with in-situ data provided from the HCMR buoy network operating in the area. Both the CMEMS Med MFC products and COASTAL CRETE forecasts are made available through a customized instance of ADAM (Advanced geospatial Data Management platform) developed by MEEO S.r.l. (https://explorer-coastal-crete.adamplatform.eu/). This application provides automatic data exchange management capabilities between the CMEMS Med MFC and the COASTAL CRETE models, enabling data visualization, combination, processing and download through the implementation of the Digital Earth concept. Among the numerous functionalities of the platform, a depth slider allows to explore the COASTAL CRETE products through the depth dimension, and a sea current magnitude feature enables the visualization of the currents vectors by overlaying them to any available product/parameter, thus allowing comparisons and correlations. The downscaled high-resolution COASTAL CRETE forecasts will be used to deliver on demand information and services in the broader objectives of the maritime safety, particularly for oil spill and floating objects/marine litters predictions. Such a use case is presented for the port area of Heraklion, implementing nested fine grid hydrodynamic and oil spill models (MEDSLIK-II).</p><p>Acknowledgement: Copernicus Marine Environment Monitoring Service (CMEMS) DEMONSTRATION COASTAL-MED SEA. COASTAL-CRETE, Contract: 110-DEM5-L3.</p>

Capturing Planned Protests from Open Source Indicators

AI Magazine ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 63-75
Author(s):  
Sathappan Muthiah ◽  
Bert Huang ◽  
Jaime Arredondo ◽  
David Mares ◽  
Lise Getoor ◽  
...  
Keyword(s):  
Social Media ◽  
News Media ◽  
Lead Time ◽  
Authoritarian Regimes ◽  
Future Time ◽  
Civil Unrest ◽  
Trade Offs ◽  
Soft Logic ◽  
Forecasting System ◽  
Average Lead

Civil unrest events (protests, strikes, and “occupy” events) are common occurrences in both democracies and authoritarian regimes. The study of civil unrest is a key topic for political scientists as it helps capture an important mechanism by which citizenry express themselves. In countries where civil unrest is lawful, qualitative analysis has revealed that more than 75 percent of the protests are planned, organized, or announced in advance; therefore detecting references to future planned events in relevant news and social media is a direct way to develop a protest forecasting system. We report on a system for doing that in this article. It uses a combination of keyphrase learning to identify what to look for, probabilistic soft logic to reason about location occurrences in extracted results, and time normalization to resolve future time mentions. We illustrate the application of our system to 10 countries in Latin America: Argentina, Brazil, Chile, Colombia, Ecuador, El Salvador, Mexico, Paraguay, Uruguay, and Venezuela. Results demonstrate our successes in capturing significant societal unrest in these countries with an average lead time of 4.08 days. We also study the selective superiorities of news media versus social media (Twitter, Facebook) to identify relevant trade-offs.

scholarly journals Seasonal forecasts of droughts in African basins using the Standardized Precipitation Index

2013 ◽  
Vol 17 (6) ◽  
pp. 2359-2373 ◽  
Author(s):  
E. Dutra ◽  
F. Di Giuseppe ◽  
F. Wetterhall ◽  
F. Pappenberger
Keyword(s):  
Real Time ◽  
Lead Time ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Seasonal Forecasting ◽  
Monthly Precipitation ◽  
Seasonal Forecasts ◽  
Blue Nile ◽  
Forecasting System ◽  
The Standardized Precipitation Index

Abstract. Vast parts of Africa rely on the rainy season for livestock and agriculture. Droughts can have a severe impact in these areas, which often have a very low resilience and limited capabilities to mitigate drought impacts. This paper assesses the predictive capabilities of an integrated drought monitoring and seasonal forecasting system (up to 5 months lead time) based on the Standardized Precipitation Index (SPI). The system is constructed by extending near-real-time monthly precipitation fields (ECMWF ERA-Interim reanalysis and the Climate Anomaly Monitoring System–Outgoing Longwave Radiation Precipitation Index, CAMS-OPI) with monthly forecasted fields as provided by the ECMWF seasonal forecasting system. The forecasts were then evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi. There are significant differences in the quality of the precipitation between the datasets depending on the catchments, and a general statement regarding the best product is difficult to make. The generally low number of rain gauges and their decrease in the recent years limits the verification and monitoring of droughts in the different basins, reinforcing the need for a strong investment on climate monitoring. All the datasets show similar spatial and temporal patterns in southern and north-western Africa, while there is a low correlation in the equatorial area, which makes it difficult to define ground truth and choose an adequate product for monitoring. The seasonal forecasts have a higher reliability and skill in the Blue Nile, Limpopo and Upper Niger in comparison with the Zambezi. This skill and reliability depend strongly on the SPI timescale, and longer timescales have more skill. The ECMWF seasonal forecasts have predictive skill which is higher than using climatology for most regions. In regions where no reliable near-real-time data is available, the seasonal forecast can be used for monitoring (first month of forecast). Furthermore, poor-quality precipitation monitoring products can reduce the potential skill of SPI seasonal forecasts in 2 to 4 months lead time.

scholarly journals Assessing the Potential of Upcoming Satellite Altimeter Missions in Operational Flood Forecasting Systems

2021 ◽  
Vol 13 (21) ◽  
pp. 4459
Author(s):  
Aline Falck ◽  
Javier Tomasella ◽  
Fabrice Papa
Keyword(s):  
Data Collection ◽  
Lead Time ◽  
Flood Forecasting ◽  
Lead Times ◽  
Latency Time ◽  
Distributed Hydrological Model ◽  
Satellite Altimeter ◽  
Operational Characteristics ◽  
Potential Benefits ◽  
Forecasting System

This study investigates the potential of observations with improved frequency and latency time of upcoming altimetry missions on the accuracy of flood forecasting and early warnings. To achieve this, we assessed the skill of the forecasts of a distributed hydrological model by assimilating different historical discharge time frequencies and latencies in a framework that mimics an operational forecast system, using the European Ensemble Forecasting system as the forcing. Numerical experiments were performed in 22 sub-basins of the Tocantins-Araguaia Basin. Forecast skills were evaluated in terms of the Relative Operational Characteristics (ROC) as a function of the drainage area and the forecasts’ lead time. The results showed that increasing the frequency of data collection and reducing the latency time (especially 1 d update and low latency) had a significant impact on steep headwater sub-basins, where floods are usually more destructive. In larger basins, although the increased frequency of data collection improved the accuracy of the forecasts, the potential benefits were limited to the earlier lead times.

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